Skip to main content

Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum


A novel approach for onset detection of musical notes from audio signals is presented. In contrast to most commonly used conventional approaches, the proposed method features new detection functions constructed from the linear temporal bases that are obtained from the decomposition of musical spectra using nonnegative matrix factorization (NMF). Three forms of detection function, namely, first-order difference function, psychoacoustically motivated relative difference function, and constant-balanced relative difference function, are considered. As the approach works directly on input data, no prior knowledge or statistical information is therefore required. Practical issues, including the choice of the factorization rank and detection robustness to instruments, are also examined experimentally. Due to the scalability issue with the generated nonnegative matrix, the proposed method is only applied to relatively short, single instrument (or voice) recordings. Numerical examples are provided to show the good performance of the proposed method, including comparisons between the three detection functions.

Publisher note

To access the full article, please see PDF.

Author information



Corresponding author

Correspondence to Wenwu Wang.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Wang, W., Luo, Y., Chambers, J.A. et al. Note Onset Detection via Nonnegative Factorization of Magnitude Spectrum. EURASIP J. Adv. Signal Process. 2008, 231367 (2008).

Download citation


  • Practical Issue
  • Audio Signal
  • Difference Function
  • Full Article
  • Temporal Basis